Abstract
Purpose: The Smart City Project aims to secure the sustainability of cities with many social problems and to improve the lives of urban residents. However, the implementation tasks and methods for realizing a smart city may vary depending on the situation of each city. If you can determine the priority and appropriate methods of each project in the smart city project, you can increase the chances of smart city implementation success. In this paper, we proposed a decision model based on AHP (Analytical Hierarchy Process) that can identify the priority of each tasks that can be included in the smart city project and the appropriate methods for driving forward each task. The proposed decision model was applied in consideration of the situation of Jeju Smart City and suggested implications through expert surveys and analysis. Research design, data and methodology: The proposed decision model is designed to apply the AHP and has a structure including three-tier factors. In the proposed decision model, the first tier corresponds to the driving area of the smart city, the second tier corresponds to the driving task, and the third tier corresponds to the deriving method. The proposed decision model was applied to the Jeju Smart City project. In the Jeju Smart City decision model, evaluation factors in each tier were derived through literature review and expert brainstorming. As an example of applying the decision model for Jeju Smart City, tourism, resident life, and industry were derived as the promotion areas included in the first tier. The promotion tasks included in the 2nd tier include electric vehicle diffusion, energy development, MaaS, safety, and garbage. Big data platform and block chain special zone were derived. As the promotion methods for each project, the government-led, private enterprise-led, join-up, and living labs were drawn. The proposed decision model can be customized for each city s situation. Conclusions: The most important driving area in Jeju Smart City was the area of resident life. The tasks of high importance were in the field of safety and garbage. As for the method of deriving tasks in the project, the proportion of the government (public) lead was high. The decision model proposed in this paper can be customized for other smart city projects and used.
Published Version
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